Abstract
Service providers embed self-customization options into their web-based service systems to facilitate user-centered service creation and consumption. The aim of this study is to demonstrate that provision of such self-customization features offers customer lock-in effects. Specifically, the study explores how the act of self-customization enhances users’ self-efficacy beliefs and perceived fit of the resulting service environment with their wants and needs. An AMOS analysis based on survey data of 600 undergraduate students indicates that (1) self-customization enhances perceived fit and self-efficacy and (2) they in turn enhance users’ motivation and continuance intention.
Similar content being viewed by others
Notes
SKcommunications, http://www.skcomms.co.kr/eng.
References
Agarwal R, Karahanna E (2000) Time flies when you’re having fun: cognitive absorption and beliefs about information technology usage. MIS Quart 24(4):665–695
Anderson JC, Gerbing DW (1988) Structural equation modeling in practice: a review and recommended two-step approach. Psychol Bull 103(3):411–423
Bagozzi RP, Yi Y, Phillips LW (1991) Assessing construct validity in organizational research. Admin Sci Quart 36(3):421–458
Bandura A (1977) Self-efficacy: toward a unifying theory of behavioral change. Psychol Rev 84(2):191–215
Bandura A (1989) Human agency in social cognitive theory. Am Psychol 44(9):1175–1184
Bandura A (1997) Self-efficacy: the exercise of control. WH Freeman, New York
Bandura A (2001) Social cognitive theory of mass communication. Media Psychol 3(3):265–299
Bandura A, Locke E (2003) Negative self-efficacy and goal effects revisited. J Appl Psychol 88(1):87–99
Bandura A, Schunk DH (1981) Cultivating competence, self-efficacy, and intrinsic interest through proximal self-motivation. J Pers Soc Psychol 41(3):586–598
Bearden WO, Sharma S, Teel JE (1982) Sample size effects on chi square and other statistics used in evaluating causal models. J Marketing Res 19(4):425–430
Bentler P, Bonnett DG (1980) Significance tests and goodness of fit in the analysis of covariance structures. Psychol Bull 88(3):588–606
Bettman JR, Luce MF, Payne JW (1998) Constructive consumer processes. J Consum Res 25(3):187–217
Bhattacherjee A, Barfar A (2011) Information technology continuance research: current state and future directions. Asia Pac J Inf Syst 21(2):1–18
Chin WW (1998) Issues and opinion on structural equation modeling. MIS Quart 21(1):7–16
Compeau D, Higgins CA, Huff S (1999) Social cognitive theory and Individual reactions to computing technology: a longitudinal study. MIS Quart 23(2):145–158
Davis FD, Bagozzi RP, Warshaw PR (1992) Extrinsic and intrinsic motivation to use computers in the workplace. J Appl Soc Psychol 22(14):1111–1132
Deci EL, Ryan RM (1985) Intrinsic motivation and self-determination in human behavior. Plenum, New York
Deci EL, Koestner R, Ryan RM (1999) A meta-analytic review of experiments examining the effects of extrinsic rewards on intrinsic motivation. Psychol Bull 125(6):627–668
del Brio JÁ, Fernández E, Junquera B (2007) Customer interaction in environmental innovation: the case of cloth diaper laundering. Serv Bus 1:141–158
Dellaert BGC, Dabholkar PA (2009) Increasing the attractiveness of mass-customization: the role of complementary online services and range of options. Int J Electron Comm 13(3):43–70
Fan H, Poole MS (2006) What is personalization? Perspectives on the design and implementation of personalization in information systems. J Org Comp Elect Comm 16(3&4):179–202
Fornell C, Larcker D (1981) Structural equation models with unobservable variables and measurement error. J Marketing Res 18(1):39–50
Franke N, Keinz P, Steger C (2009) Testing the value of customization: when do customers really prefer products tailored to their preferences? J Marketing 73(5):103–121
Franke N, Schreier M, Kaiser U (2010) The I designed it myself effect in mass customization. Manage Sci 56(1):125–140
Gretzel U, Fesenmaier DR (2006) Persuasion in recommender systems. Int J Electron Comm 11(2):81–100
Hasan B (2006) Delineating the effects of general and system-specific computer self-efficacy beliefs on IS acceptance. Inform Manage 43:565–571
Hayduk LA (1987) Structural equation modeling with LISREL: essentials and advances. Johns Hopkins University Press, Baltimore
Hsu MH, Chiu CM (2004) Predicting electronic service continuance with a decomposed theory of planned behavior. Behav Inform Technol 23(5):359–373
Igbaria M, Parasuraman S, Baroudi JJ (1996) A motivational model of microcomputer usage. J Manage Inform Syst 13(1):127–143
Kamis A, Koufaris M, Stern T (2008) Using an attribute-based decision support system for user-customized products online: an experimental investigation. MIS Quart 32(1):159–177
Kang YS, Hong S, Lee H (2009) Exploring continued online service usage behavior: the roles of self-image congruity and regret. Comput Hum Behav 25(1):111–122
Korpipää P, Malm EJ, Rantakokko T, Kyllönen V, Kela J, Mäntyjärvi J, Häkkilä J, Känsälä I (2006) Customizing user interaction in smart phones. IEEE Pervasive Comput 5(3):82–90
Koufaris M (2002) Applying the technology acceptance model and flow theory to online consumer behavior. Inform Syst Res 13(2):205–224
Kramer T (2007) The effect of measurement task transparency on preference construction and evaluations of personalized recommendations. J Marketing Res 44(2):224–233
Kumar N, Benbasat I (2006) The influence of recommendations and consumer reviews on evaluations of websites. Inform Syst Res 17(4):425-439
Lee HH, Chang EY (2011) Consumer attitudes toward online mass customization: an application of extended technology acceptance model. J Comput-Mediat Comm 16(2):171–200
Lee MKO, Cheung CMK, Chen Z (2005) Acceptance of internet-based learning medium; the role of extrinsic and intrinsic motivation. Inform Manage 42(8):1095–1104
Liang H, Saraf N, Hu Q, Xue Y (2007) Assimilation of enterprise systems: the effect of institutional pressures and the mediating role of top management. MIS Quart 31(1):59–87
Lin CS, Wu S, Tsai RJ (2005) Integrating perceived playfulness into expectation-confirmation model for web portal context. Inform Manage 42(5):683–693
Mathieu JE, Martineau JW, Tannenbaum SI (1993) Individual and situational influences on the development of self efficacy: implications for training effectiveness. Pers Psychol 46(1):125–147
McKee D, Simmers CS, Licata J (2006) Customer self-efficacy and response to service. J Serv Res 8(3):207–220
Meuter ML, Bitner MJ, Ostrom AL, Brown SW (2005) Choosing among alternative service delivery modes: an investigation of customer trial of self-service technologies. J Marketing 69(2):61–83
Millar MG, Millar KU (1996) The effects of direct and indirect experience on affective and cognitive responses and the attitude–behavior relation. J Exp Soc Psychol 32(6):561–579
Monk AF, Blom JO (2007) A theory of personalization of appearance: quantitative evaluation of qualitatively derived data. Behav Inform Technol 26(3):237–246
Norton MI (2009) The IKEA effect: when labor leads to love. Harvard Bus Rev 87(2):30–34
Novak TP, Hoffman DL, Yung YF (2000) Measuring the customer experience in online environments: a structural modeling approach. Market Sci 19(1):22–42
Nunnally JC (1978) Psychometric theory. McGraw-Hill, New York
Podsakoff PM, Organ DW (1986) Self-reports in organizational research: problems and prospects. J Manage 12(4):531–544
Randall T, Terwiesch C, Ulrich KT (2007) User design of customized products. Market Sci 26(2):268–283
Roca JC, Gagné M (2008) Understanding e-learning continuance intention in the workplace: a self-determination theory perspective. Comput Hum Behav 24(4):1585–1604
Schreier M (2006) The value increment of mass-customized products: an empirical assessment. J Consum Behav 5:317–327
Shang RA, Chen YC, Shen L (2005) Extrinsic versus intrinsic motivations for consumers to shop on-line. Inform Manage 42(3):401–413
Simonson I (2005) Determinants of customers’ responses to customized offers: conceptual framework and research propositions. J Marketing 69(1):32–45
Sundar SS, Marathe SS (2010) Personalization versus customization: the importance of agency, privacy, and power usage. Hum Comm Res 36(3):298–322
Teo TSH, Lim VKG, Lai RYC (1999) Intrinsic and extrinsic motivation in internet usage. Omega 27(1):25–37
Thong JYL, Hong SJ, Tam KY (2006) The effects of post-adoption beliefs on the expectation-confirmation model for information technology continuance. Int J Hum-Comput St 64(9):799–810
Valenzuela A, Dhar R, Zettelmeyer F (2009) Contingent response to self-customization procedures: implications for decision satisfaction and choice. J Marketing Res 46(6):754–763
Van Beuningen J, Ruyter KD, Wetzels M, Streukens S (2009) Customer self-efficacy in technology-based self-service: assessing between- and within-person differences. J Serv Res 11(4):407–428
Van der Heijden H (2004) User acceptance of hedonic information systems. MIS Quart 28(4):695–704
Venkatesh V (2000) Determinants of perceived ease of use: integrating control, intrinsic motivation, and emotion into the technology acceptance model. Inform Sys Res 11(4):342–365
Wu JH, Chen YC, Lin LM (2007) Empirical evaluation of the revised end user computing acceptance model. Comput Hum Behav 23(1):162–174
Zhao X, Mattila AS, Tao LE (2008) The role of post-training self-efficacy in customers’ use of self service technologies. Int J Serv Ind Manage 19(4):492–505
Acknowledgments
This article was supported by Faculty Research Fund, Sungkyunkwan University, 2010.
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Kang, Y.J., Lee, W.J. Self-customization of online service environments by users and its effect on their continuance intention. Serv Bus 9, 321–342 (2015). https://doi.org/10.1007/s11628-014-0229-y
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s11628-014-0229-y